NSF2026: EAGER: Collaborative Research: Enhancing Employment for Neurodiverse Individuals through Next-Generation, AI-Enabled Assessments of Visuospatial Cognition

在美国，每年大约有 70,000 名患有自闭症谱系的成年人寻求就业。 与此同时，技术、金融、医疗保健和许多其他关键工作领域的雇主寻求高技能和训练有素的个人来填补专业职位。在学习研究部 DRK-12 计划和综合活动办公室 NSF 2026 基金计划的支持下，这项研究将研究新的工具和方法，将自闭症谱系个体求职者与利用其独特认知技能的就业机会相匹配，重点关注视觉空间认知技能。 许多工作都需要强大的视觉空间认知技能，例如视觉检查和质量控制、过程监控、文档审查、监视、软件测试和数据可视化等。 许多自闭症患者都表现出视觉空间认知技能的优势，但这些优势尚未得到充分理解，包括它们因人而异以及它们如何映射到工作场所相关能力。 了解自闭症谱系或其他神经多样性状况的个人的视觉空间认知技能，可以通过在公共和私营部门制定更有效的招聘、选择和保留此类候选人的计划，对增强劳动力的神经多样性产生巨大的潜在影响。 这个 NSF2026 EAGER 项目丰富了 NSF2026 Idea Machine 获奖作品《Harnessing the Human Diversity of Mind》。它寻求开发和评估集成的人工智能技术，以新的方式测量一个人的视觉空间认知技能，然后使用这些测量来预测工作场所相关任务的表现。 在这个为期两年的项目中进行的研究将包括对自闭症谱系个体和神经典型个体进行大型试点研究，其中参与者将接受多次视觉空间测试，并使用眼动仪和相机等传感器记录有关他们行为的详细数据。然后，数据挖掘和机器学习技术将用于从这些丰富的行为数据流中提取有意义的模式，并进行分析以检查这些基本行为模式如何映射到现实的、工作场所相关活动中的个人技能和兴趣。 这项研究还将收集和分析行业合作伙伴的详细反馈，以确定可以从招聘视觉空间认知技能较强的员工中受益的特定工作类型和部门。 此外，该项目将让神经多样性学生和工作人员参与其许多活动，特别是让受 NSF 研究实习生神经多样性启发科学与工程 (NISE) 支持的研究生学员参与，并利用范德比尔特大学工程学院自闭症与创新中心神经多样性实习生的技能。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Each year in the United States, approximately 70,000 new adults on the autism spectrum will seek employment. At the same time, employers in technology, finance, healthcare, and many other critical job sectors seek highly skilled and highly trained individuals to fill specialized positions. With support from the DRK-12 Program in the Division of Research on Learning and the NSF 2026 Fund Program in the Office of Integrated Activities, this research will investigate new tools and methods for matching individual job-seekers on the autism spectrum to employment opportunities that leverage their unique cognitive skills, with a focus on visuospatial cognitive skills. Numerous jobs require strong visuospatial cognitive skills, such as visual inspection and quality control, process monitoring, document review, surveillance, software testing, and data visualization, to name a few. Many people on the autism spectrum show strengths in visuospatial cognitive skills, but these strengths are not fully understood, including how they differ from person to person and how they map onto workplace-relevant capabilities. Understanding visuospatial cognitive skills in individuals on the autism spectrum or other neurodiverse conditions has high potential impact for enhancing the neurodiversity of the workforce by enabling more effective programs for the recruitment, selection, and retention of such candidates in the public and private sectors. This NSF2026 EAGER project enriches the NSF2026 Idea Machine winning entry Harnessing the Human Diversity of Mind. It seeks to develop and evaluate integrated, AI-enabled technologies for measuring a person’s visuospatial cognitive skills in new ways and then using these measurements to predict performance on workplace-relevant tasks. The research conducted during this two-year project will include conducting a large pilot study with individuals on the autism spectrum and neurotypical individuals, in which participants will be given several visuospatial tests, and detailed data about their actions will be recorded using sensors such as eye trackers and cameras. Then, data mining and machine learning techniques will be used to extract meaningful patterns from these rich streams of behavioral data, and analyses will be conducted to examine how these patterns in foundational behaviors map onto individual skills and interests in realistic, workplace-relevant activities. This research will also gather and analyze detailed feedback from industry partners to identify specific job types and sectors that would benefit from recruiting employees who are strong in visuospatial cognitive skills. In addition, this project will involve neurodiverse students and staff in many of its activities, in particular by involving graduate trainees supported by the NSF Research Traineeship in Neurodiversity Inspired Science & Engineering (NISE) and by leveraging the skills of neurodiverse interns at the Frist Center for Autism & Innovation at Vanderbilt University's School of Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.